Project acronym 3DWATERWAVES
Project Mathematical aspects of three-dimensional water waves with vorticity
Researcher (PI) Erik Torsten Wahlen
Host Institution (HI) LUNDS UNIVERSITET
Country Sweden
Call Details Starting Grant (StG), PE1, ERC-2015-STG
Summary The goal of this project is to develop a mathematical theory for steady three-dimensional water waves with vorticity. The mathematical model consists of the incompressible Euler equations with a free surface, and vorticity is important for modelling the interaction of surface waves with non-uniform currents. In the two-dimensional case, there has been a lot of progress on water waves with vorticity in the last decade. This progress has mainly been based on the stream function formulation, in which the problem is reformulated as a nonlinear elliptic free boundary problem. An analogue of this formulation is not available in three dimensions, and the theory has therefore so far been restricted to irrotational flow. In this project we seek to go beyond this restriction using two different approaches. In the first approach we will adapt methods which have been used to construct three-dimensional ideal flows with vorticity in domains with a fixed boundary to the free boundary context (for example Beltrami flows). In the second approach we will develop methods which are new even in the case of a fixed boundary, by performing a detailed study of the structure of the equations close to a given shear flow using ideas from infinite-dimensional bifurcation theory. This involves handling infinitely many resonances.
Summary
The goal of this project is to develop a mathematical theory for steady three-dimensional water waves with vorticity. The mathematical model consists of the incompressible Euler equations with a free surface, and vorticity is important for modelling the interaction of surface waves with non-uniform currents. In the two-dimensional case, there has been a lot of progress on water waves with vorticity in the last decade. This progress has mainly been based on the stream function formulation, in which the problem is reformulated as a nonlinear elliptic free boundary problem. An analogue of this formulation is not available in three dimensions, and the theory has therefore so far been restricted to irrotational flow. In this project we seek to go beyond this restriction using two different approaches. In the first approach we will adapt methods which have been used to construct three-dimensional ideal flows with vorticity in domains with a fixed boundary to the free boundary context (for example Beltrami flows). In the second approach we will develop methods which are new even in the case of a fixed boundary, by performing a detailed study of the structure of the equations close to a given shear flow using ideas from infinite-dimensional bifurcation theory. This involves handling infinitely many resonances.
Max ERC Funding
1 203 627 €
Duration
Start date: 2016-03-01, End date: 2022-02-28
Project acronym AcetyLys
Project Unravelling the role of lysine acetylation in the regulation of glycolysis in cancer cells through the development of synthetic biology-based tools
Researcher (PI) Eyal Arbely
Host Institution (HI) BEN-GURION UNIVERSITY OF THE NEGEV
Country Israel
Call Details Starting Grant (StG), LS9, ERC-2015-STG
Summary Synthetic biology is an emerging discipline that offers powerful tools to control and manipulate fundamental processes in living matter. We propose to develop and apply such tools to modify the genetic code of cultured mammalian cells and bacteria with the aim to study the role of lysine acetylation in the regulation of metabolism and in cancer development. Thousands of lysine acetylation sites were recently discovered on non-histone proteins, suggesting that acetylation is a widespread and evolutionarily conserved post translational modification, similar in scope to phosphorylation and ubiquitination. Specifically, it has been found that most of the enzymes of metabolic processes—including glycolysis—are acetylated, implying that acetylation is key regulator of cellular metabolism in general and in glycolysis in particular. The regulation of metabolic pathways is of particular importance to cancer research, as misregulation of metabolic pathways, especially upregulation of glycolysis, is common to most transformed cells and is now considered a new hallmark of cancer. These data raise an immediate question: what is the role of acetylation in the regulation of glycolysis and in the metabolic reprogramming of cancer cells? While current methods rely on mutational analyses, we will genetically encode the incorporation of acetylated lysine and directly measure the functional role of each acetylation site in cancerous and non-cancerous cell lines. Using this methodology, we will study the structural and functional implications of all the acetylation sites in glycolytic enzymes. We will also decipher the mechanism by which acetylation is regulated by deacetylases and answer a long standing question – how 18 deacetylases recognise their substrates among thousands of acetylated proteins? The developed methodologies can be applied to a wide range of protein families known to be acetylated, thereby making this study relevant to diverse research fields.
Summary
Synthetic biology is an emerging discipline that offers powerful tools to control and manipulate fundamental processes in living matter. We propose to develop and apply such tools to modify the genetic code of cultured mammalian cells and bacteria with the aim to study the role of lysine acetylation in the regulation of metabolism and in cancer development. Thousands of lysine acetylation sites were recently discovered on non-histone proteins, suggesting that acetylation is a widespread and evolutionarily conserved post translational modification, similar in scope to phosphorylation and ubiquitination. Specifically, it has been found that most of the enzymes of metabolic processes—including glycolysis—are acetylated, implying that acetylation is key regulator of cellular metabolism in general and in glycolysis in particular. The regulation of metabolic pathways is of particular importance to cancer research, as misregulation of metabolic pathways, especially upregulation of glycolysis, is common to most transformed cells and is now considered a new hallmark of cancer. These data raise an immediate question: what is the role of acetylation in the regulation of glycolysis and in the metabolic reprogramming of cancer cells? While current methods rely on mutational analyses, we will genetically encode the incorporation of acetylated lysine and directly measure the functional role of each acetylation site in cancerous and non-cancerous cell lines. Using this methodology, we will study the structural and functional implications of all the acetylation sites in glycolytic enzymes. We will also decipher the mechanism by which acetylation is regulated by deacetylases and answer a long standing question – how 18 deacetylases recognise their substrates among thousands of acetylated proteins? The developed methodologies can be applied to a wide range of protein families known to be acetylated, thereby making this study relevant to diverse research fields.
Max ERC Funding
1 499 375 €
Duration
Start date: 2016-07-01, End date: 2022-06-30
Project acronym ACO
Project The Proceedings of the Ecumenical Councils from Oral Utterance to Manuscript Edition as Evidence for Late Antique Persuasion and Self-Representation Techniques
Researcher (PI) Peter Alfred Riedlberger
Host Institution (HI) OTTO-FRIEDRICH-UNIVERSITAET BAMBERG
Country Germany
Call Details Starting Grant (StG), SH5, ERC-2015-STG
Summary The Acts of the Ecumenical Councils of Late Antiquity include (purportedly) verbatim minutes of the proceedings, a formal framework and copies of relevant documents which were either (allegedly) read out during the proceedings or which were later attached to the Acts proper. Despite this unusual wealth of documentary evidence, the daunting nature of the Acts demanding multidisciplinary competency, their complex structure with a matryoshka-like nesting of proceedings from different dates, and the stereotype that their contents bear only on Christological niceties have deterred generations of historians from studying them. Only in recent years have their fortunes begun to improve, but this recent research has not always been based on sound principles: the recorded proceedings of the sessions are still often accepted as verbatim minutes. Yet even a superficial reading quickly reveals widespread editorial interference. We must accept that in many cases the Acts will teach us less about the actual debates than about the editors who shaped their presentation. This does not depreciate the Acts’ evidence: on the contrary, they are first-rate material for the rhetoric of persuasion and self-representation. It is possible, in fact, to take the investigation to a deeper level and examine in what manner the oral proceedings were put into writing: several passages in the Acts comment upon the process of note-taking and the work of the shorthand writers. Thus, the main objective of the proposed research project could be described as an attempt to trace the destinies of the Acts’ texts, from the oral utterance to the manuscript texts we have today. This will include the fullest study on ancient transcript techniques to date; a structural analysis of the Acts’ texts with the aim of highlighting edited passages; and a careful comparison of the various editions of the Acts, which survive in Greek, Latin, Syriac and Coptic, in order to detect traces of editorial interference.
Summary
The Acts of the Ecumenical Councils of Late Antiquity include (purportedly) verbatim minutes of the proceedings, a formal framework and copies of relevant documents which were either (allegedly) read out during the proceedings or which were later attached to the Acts proper. Despite this unusual wealth of documentary evidence, the daunting nature of the Acts demanding multidisciplinary competency, their complex structure with a matryoshka-like nesting of proceedings from different dates, and the stereotype that their contents bear only on Christological niceties have deterred generations of historians from studying them. Only in recent years have their fortunes begun to improve, but this recent research has not always been based on sound principles: the recorded proceedings of the sessions are still often accepted as verbatim minutes. Yet even a superficial reading quickly reveals widespread editorial interference. We must accept that in many cases the Acts will teach us less about the actual debates than about the editors who shaped their presentation. This does not depreciate the Acts’ evidence: on the contrary, they are first-rate material for the rhetoric of persuasion and self-representation. It is possible, in fact, to take the investigation to a deeper level and examine in what manner the oral proceedings were put into writing: several passages in the Acts comment upon the process of note-taking and the work of the shorthand writers. Thus, the main objective of the proposed research project could be described as an attempt to trace the destinies of the Acts’ texts, from the oral utterance to the manuscript texts we have today. This will include the fullest study on ancient transcript techniques to date; a structural analysis of the Acts’ texts with the aim of highlighting edited passages; and a careful comparison of the various editions of the Acts, which survive in Greek, Latin, Syriac and Coptic, in order to detect traces of editorial interference.
Max ERC Funding
1 497 250 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym Age Asymmetry
Project Age-Selective Segregation of Organelles
Researcher (PI) Pekka Aleksi Katajisto
Host Institution (HI) HELSINGIN YLIOPISTO
Country Finland
Call Details Starting Grant (StG), LS3, ERC-2015-STG
Summary Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage.
I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging.
We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.
Summary
Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage.
I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging.
We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym Antibodyomics
Project Vaccine profiling and immunodiagnostic discovery by high-throughput antibody repertoire analysis
Researcher (PI) Sai Tota Reddy
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Country Switzerland
Call Details Starting Grant (StG), LS7, ERC-2015-STG
Summary Vaccines and immunodiagnostics have been vital for public health and medicine, however a quantitative molecular understanding of vaccine-induced antibody responses is lacking. Antibody research is currently going through a big-data driven revolution, largely due to progress in next-generation sequencing (NGS) and bioinformatic analysis of antibody repertoires. A main advantage of high-throughput antibody repertoire analysis is that it provides a wealth of quantitative information not possible with other classical methods of antibody analysis (i.e., serum titers); this information includes: clonal distribution and diversity, somatic hypermutation patterns, and lineage tracing. In preliminary work my group has established standardized methods for antibody repertoire NGS, including an experimental-bioinformatic pipeline for error and bias correction that enables highly accurate repertoire sequencing and analysis. The overall goal of this proposal will be to apply high-throughput antibody repertoire analysis for quantitative vaccine profiling and discovery of next-generation immunodiagnostics. Using mouse subunit vaccination as our model system, we will answer for the first time, a fundamental biological question within the context of antibody responses - what is the link between genotype (antibody repertoire) and phenotype (serum antibodies)? We will expand upon this approach for improved rational vaccine design by quantitatively determining the impact of a comprehensive set of subunit vaccination parameters on complete antibody landscapes. Finally, we will develop advanced bioinformatic methods to discover immunodiagnostics based on antibody repertoire sequences. In summary, this proposal lays the foundation for fundamentally new approaches in the quantitative analysis of antibody responses, which long-term will promote the development of next-generation vaccines and immunodiagnostics.
Summary
Vaccines and immunodiagnostics have been vital for public health and medicine, however a quantitative molecular understanding of vaccine-induced antibody responses is lacking. Antibody research is currently going through a big-data driven revolution, largely due to progress in next-generation sequencing (NGS) and bioinformatic analysis of antibody repertoires. A main advantage of high-throughput antibody repertoire analysis is that it provides a wealth of quantitative information not possible with other classical methods of antibody analysis (i.e., serum titers); this information includes: clonal distribution and diversity, somatic hypermutation patterns, and lineage tracing. In preliminary work my group has established standardized methods for antibody repertoire NGS, including an experimental-bioinformatic pipeline for error and bias correction that enables highly accurate repertoire sequencing and analysis. The overall goal of this proposal will be to apply high-throughput antibody repertoire analysis for quantitative vaccine profiling and discovery of next-generation immunodiagnostics. Using mouse subunit vaccination as our model system, we will answer for the first time, a fundamental biological question within the context of antibody responses - what is the link between genotype (antibody repertoire) and phenotype (serum antibodies)? We will expand upon this approach for improved rational vaccine design by quantitatively determining the impact of a comprehensive set of subunit vaccination parameters on complete antibody landscapes. Finally, we will develop advanced bioinformatic methods to discover immunodiagnostics based on antibody repertoire sequences. In summary, this proposal lays the foundation for fundamentally new approaches in the quantitative analysis of antibody responses, which long-term will promote the development of next-generation vaccines and immunodiagnostics.
Max ERC Funding
1 492 586 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym ARCA
Project Analysis and Representation of Complex Activities in Videos
Researcher (PI) Juergen Gall
Host Institution (HI) RHEINISCHE FRIEDRICH-WILHELMS-UNIVERSITAT BONN
Country Germany
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary The goal of the project is to automatically analyse human activities observed in videos. Any solution to this problem will allow the development of novel applications. It could be used to create short videos that summarize daily activities to support patients suffering from Alzheimer's disease. It could also be used for education, e.g., by providing a video analysis for a trainee in the hospital that shows if the tasks have been correctly executed.
The analysis of complex activities in videos, however, is very challenging since activities vary in temporal duration between minutes and hours, involve interactions with several objects that change their appearance and shape, e.g., food during cooking, and are composed of many sub-activities, which can happen at the same time or in various orders.
While the majority of recent works in action recognition focuses on developing better feature encoding techniques for classifying sub-activities in short video clips of a few seconds, this project moves forward and aims to develop a higher level representation of complex activities to overcome the limitations of current approaches. This includes the handling of large time variations and the ability to recognize and locate complex activities in videos. To this end, we aim to develop a unified model that provides detailed information about the activities and sub-activities in terms of time and spatial location, as well as involved pose motion, objects and their transformations.
Another aspect of the project is to learn a representation from videos that is not tied to a specific source of videos or limited to a specific application. Instead we aim to learn a representation that is invariant to a perspective change, e.g., from a third-person perspective to an egocentric perspective, and can be applied to various modalities like videos or depth data without the need of collecting massive training data for all modalities. In other words, we aim to learn the essence of activities.
Summary
The goal of the project is to automatically analyse human activities observed in videos. Any solution to this problem will allow the development of novel applications. It could be used to create short videos that summarize daily activities to support patients suffering from Alzheimer's disease. It could also be used for education, e.g., by providing a video analysis for a trainee in the hospital that shows if the tasks have been correctly executed.
The analysis of complex activities in videos, however, is very challenging since activities vary in temporal duration between minutes and hours, involve interactions with several objects that change their appearance and shape, e.g., food during cooking, and are composed of many sub-activities, which can happen at the same time or in various orders.
While the majority of recent works in action recognition focuses on developing better feature encoding techniques for classifying sub-activities in short video clips of a few seconds, this project moves forward and aims to develop a higher level representation of complex activities to overcome the limitations of current approaches. This includes the handling of large time variations and the ability to recognize and locate complex activities in videos. To this end, we aim to develop a unified model that provides detailed information about the activities and sub-activities in terms of time and spatial location, as well as involved pose motion, objects and their transformations.
Another aspect of the project is to learn a representation from videos that is not tied to a specific source of videos or limited to a specific application. Instead we aim to learn a representation that is invariant to a perspective change, e.g., from a third-person perspective to an egocentric perspective, and can be applied to various modalities like videos or depth data without the need of collecting massive training data for all modalities. In other words, we aim to learn the essence of activities.
Max ERC Funding
1 499 875 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym AXIAL.EC
Project PRINCIPLES OF AXIAL POLARITY-DRIVEN VASCULAR PATTERNING
Researcher (PI) Claudio Franco
Host Institution (HI) INSTITUTO DE MEDICINA MOLECULAR JOAO LOBO ANTUNES
Country Portugal
Call Details Starting Grant (StG), LS4, ERC-2015-STG
Summary The formation of a functional patterned vascular network is essential for development, tissue growth and organ physiology. Several human vascular disorders arise from the mis-patterning of blood vessels, such as arteriovenous malformations, aneurysms and diabetic retinopathy. Although blood flow is recognised as a stimulus for vascular patterning, very little is known about the molecular mechanisms that regulate endothelial cell behaviour in response to flow and promote vascular patterning.
Recently, we uncovered that endothelial cells migrate extensively in the immature vascular network, and that endothelial cells polarise against the blood flow direction. Here, we put forward the hypothesis that vascular patterning is dependent on the polarisation and migration of endothelial cells against the flow direction, in a continuous flux of cells going from low-shear stress to high-shear stress regions. We will establish new reporter mouse lines to observe and manipulate endothelial polarity in vivo in order to investigate how polarisation and coordination of endothelial cells movements are orchestrated to generate vascular patterning. We will manipulate cell polarity using mouse models to understand the importance of cell polarisation in vascular patterning. Also, using a unique zebrafish line allowing analysis of endothelial cell polarity, we will perform a screen to identify novel regulators of vascular patterning. Finally, we will explore the hypothesis that defective flow-dependent endothelial polarisation underlies arteriovenous malformations using two genetic models.
This integrative approach, based on high-resolution imaging and unique experimental models, will provide a unifying model defining the cellular and molecular principles involved in vascular patterning. Given the physiological relevance of vascular patterning in health and disease, this research plan will set the basis for the development of novel clinical therapies targeting vascular disorders.
Summary
The formation of a functional patterned vascular network is essential for development, tissue growth and organ physiology. Several human vascular disorders arise from the mis-patterning of blood vessels, such as arteriovenous malformations, aneurysms and diabetic retinopathy. Although blood flow is recognised as a stimulus for vascular patterning, very little is known about the molecular mechanisms that regulate endothelial cell behaviour in response to flow and promote vascular patterning.
Recently, we uncovered that endothelial cells migrate extensively in the immature vascular network, and that endothelial cells polarise against the blood flow direction. Here, we put forward the hypothesis that vascular patterning is dependent on the polarisation and migration of endothelial cells against the flow direction, in a continuous flux of cells going from low-shear stress to high-shear stress regions. We will establish new reporter mouse lines to observe and manipulate endothelial polarity in vivo in order to investigate how polarisation and coordination of endothelial cells movements are orchestrated to generate vascular patterning. We will manipulate cell polarity using mouse models to understand the importance of cell polarisation in vascular patterning. Also, using a unique zebrafish line allowing analysis of endothelial cell polarity, we will perform a screen to identify novel regulators of vascular patterning. Finally, we will explore the hypothesis that defective flow-dependent endothelial polarisation underlies arteriovenous malformations using two genetic models.
This integrative approach, based on high-resolution imaging and unique experimental models, will provide a unifying model defining the cellular and molecular principles involved in vascular patterning. Given the physiological relevance of vascular patterning in health and disease, this research plan will set the basis for the development of novel clinical therapies targeting vascular disorders.
Max ERC Funding
1 618 750 €
Duration
Start date: 2016-09-01, End date: 2022-02-28
Project acronym BARCODE DIAGNOSTICS
Project Next-Generation Personalized Diagnostic Nanotechnologies for Predicting Response to Cancer Medicine
Researcher (PI) Avraham Dror Schroeder
Host Institution (HI) TECHNION - ISRAEL INSTITUTE OF TECHNOLOGY
Country Israel
Call Details Starting Grant (StG), LS7, ERC-2015-STG
Summary Cancer is the leading cause of death in the Western world and the second cause of death worldwide. Despite advances in medical research, 30% of cancer patients are prescribed a medication the tumor does not respond to, or, alternatively, drugs that induce adverse side effects patients' cannot tolerate.
Nanotechnologies are becoming impactful therapeutic tools, granting tissue-targeting and cellular precision that cannot be attained using systems of larger scale.
In this proposal, I plan to expand far beyond the state-of-the-art and develop a conceptually new approach in which diagnostic nanoparticles are designed to retrieve drug-sensitivity information from malignant tissue inside the body. The ultimate goal of this program is to be able to predict, ahead of time, which treatment will be best for each cancer patient – an emerging field called personalized medicine. This interdisciplinary research program will expand our understandings and capabilities in nanotechnology, cancer biology and medicine.
To achieve this goal, I will engineer novel nanotechnologies that autonomously maneuver, target and diagnose the various cells that compose the tumor microenvironment and its disseminated metastasis. Each nanometric system will contain a miniscule amount of a biologically-active agent, and will serve as a nano lab for testing the activity of the agents inside the tumor cells.
To distinguish between system to system, and to grant single-cell sensitivity in vivo, nanoparticles will be barcoded with unique DNA fragments.
We will enable nanoparticle' deep tissue penetration into primary tumors and metastatic microenvironments using enzyme-loaded particles, and study how different agents, including small-molecule drugs, proteins and RNA, interact with the malignant and stromal cells that compose the cancerous microenvironments. Finally, we will demonstrate the ability of barcoded nanoparticles to predict adverse, life-threatening, side effects, in a personalized manner.
Summary
Cancer is the leading cause of death in the Western world and the second cause of death worldwide. Despite advances in medical research, 30% of cancer patients are prescribed a medication the tumor does not respond to, or, alternatively, drugs that induce adverse side effects patients' cannot tolerate.
Nanotechnologies are becoming impactful therapeutic tools, granting tissue-targeting and cellular precision that cannot be attained using systems of larger scale.
In this proposal, I plan to expand far beyond the state-of-the-art and develop a conceptually new approach in which diagnostic nanoparticles are designed to retrieve drug-sensitivity information from malignant tissue inside the body. The ultimate goal of this program is to be able to predict, ahead of time, which treatment will be best for each cancer patient – an emerging field called personalized medicine. This interdisciplinary research program will expand our understandings and capabilities in nanotechnology, cancer biology and medicine.
To achieve this goal, I will engineer novel nanotechnologies that autonomously maneuver, target and diagnose the various cells that compose the tumor microenvironment and its disseminated metastasis. Each nanometric system will contain a miniscule amount of a biologically-active agent, and will serve as a nano lab for testing the activity of the agents inside the tumor cells.
To distinguish between system to system, and to grant single-cell sensitivity in vivo, nanoparticles will be barcoded with unique DNA fragments.
We will enable nanoparticle' deep tissue penetration into primary tumors and metastatic microenvironments using enzyme-loaded particles, and study how different agents, including small-molecule drugs, proteins and RNA, interact with the malignant and stromal cells that compose the cancerous microenvironments. Finally, we will demonstrate the ability of barcoded nanoparticles to predict adverse, life-threatening, side effects, in a personalized manner.
Max ERC Funding
1 499 250 €
Duration
Start date: 2016-04-01, End date: 2022-03-31
Project acronym BEACON
Project Hybrid Digital-Analog Networking under Extreme Energy and Latency Constraints
Researcher (PI) Deniz Gunduz
Host Institution (HI) IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Country United Kingdom
Call Details Starting Grant (StG), PE7, ERC-2015-STG
Summary The objective of the BEACON project is to (re-)introduce analog communications into the design of modern wireless networks. We argue that the extreme energy and latency constraints imposed by the emerging Internet of Everything (IoE) paradigm can only be met within a hybrid digital-analog communications framework. Current network architectures separate source and channel coding, orthogonalize users, and employ long block-length digital source and channel codes, which are either suboptimal or not applicable under the aforementioned constraints. BEACON questions these well-established design principles, and proposes to replace them with a hybrid digital-analog communications framework, which will meet the required energy and latency constraints while simplifying the encoding and decoding processes. BEACON pushes the performance of the IoE to its theoretical limits by i) exploiting signal correlations that are abundant in IoE applications, given the foreseen density of deployed sensing devices, ii) taking into account the limited and stochastic nature of energy availability due to, for example, energy harvesting capabilities, iii) using feedback resources to improve the end-to-end signal distortion, and iv) deriving novel converse results to identify fundamental performance benchmarks.
The results of BEACON will not only shed light on the fundamental limits on the performance any coding scheme can achieve, but will also lead to the development of unconventional codes and communication protocols that can approach these limits, combining digital and analog communication techniques. The ultimate challenge for this project is to exploit the developed hybrid digital-analog networking theory for a complete overhaul of the physical layer design for emerging IoE applications, such as smart grids, tele-robotics and smart homes. For this purpose, a proof-of-concept implementation test-bed will also be built using software defined radios and sensor nodes.
Summary
The objective of the BEACON project is to (re-)introduce analog communications into the design of modern wireless networks. We argue that the extreme energy and latency constraints imposed by the emerging Internet of Everything (IoE) paradigm can only be met within a hybrid digital-analog communications framework. Current network architectures separate source and channel coding, orthogonalize users, and employ long block-length digital source and channel codes, which are either suboptimal or not applicable under the aforementioned constraints. BEACON questions these well-established design principles, and proposes to replace them with a hybrid digital-analog communications framework, which will meet the required energy and latency constraints while simplifying the encoding and decoding processes. BEACON pushes the performance of the IoE to its theoretical limits by i) exploiting signal correlations that are abundant in IoE applications, given the foreseen density of deployed sensing devices, ii) taking into account the limited and stochastic nature of energy availability due to, for example, energy harvesting capabilities, iii) using feedback resources to improve the end-to-end signal distortion, and iv) deriving novel converse results to identify fundamental performance benchmarks.
The results of BEACON will not only shed light on the fundamental limits on the performance any coding scheme can achieve, but will also lead to the development of unconventional codes and communication protocols that can approach these limits, combining digital and analog communication techniques. The ultimate challenge for this project is to exploit the developed hybrid digital-analog networking theory for a complete overhaul of the physical layer design for emerging IoE applications, such as smart grids, tele-robotics and smart homes. For this purpose, a proof-of-concept implementation test-bed will also be built using software defined radios and sensor nodes.
Max ERC Funding
1 496 350 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym BIGCODE
Project Learning from Big Code: Probabilistic Models, Analysis and Synthesis
Researcher (PI) Martin Vechev
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Country Switzerland
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Summary
The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
